Abstract:
The Government of the Republic of Indonesia in 2017 established the National
Strategy (STRANAS) as a form of government effort in accelerating the reduction of
stunting in Indonesia. Through the STRANAS, the government succeeded in reducing
the stunting rate in Indonesia with the prevalence of stunting from 32.7% in 2013 to
27.67% in 2019. The government has targeted that in 2024 the stunting prevalence rate
in Indonesia can decrease to 14 percent. It means that the government should be able to
reduce the prevalence rate every year by 2.7%. Based on data from the Pekanbaru City
Health Office, in 2021 the area with the highest stunting locus is in Lima Puluh
Subdistrict with a stunting prevalence of 7.29%. In this case, the Lima Puluh Health
Center, which is responsible for the main health services in handling stunting problems
in Lima Puluh District, has made efforts to monitor the nutritional health conditions of
toddlers in accordance with the program provided by the government by opening
posyandu services every month. However, problems were found, namely delays in data
delivery by posyandu cadres and data input by puskesmas health workers making
monitoring of the nutritional health of children under five too late. Therefore, this study
was conducted to predict children at risk of stunting using the nave Bayes algorithm
and the accuracy of the algorithm was measured using a confusion matrix. Training
data and testing data are divided using K-fold cross validation. Based on the results of
research using 830 data, the best accuracy is found in fold 5 with an accuracy
presentation of 73% and is implemented in a web-based programming system.
